Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma

Brian A Walker, Eileen M Boyle, Christopher P Wardell, Alex Murison, Dil B Begum, Nasrin M Dahir, Paula Z Proszek, David C Johnson, Martin F Kaiser, Lorenzo Melchor, Lauren I Aronson, Matthew Scales, Charlotte Pawlyn, Fabio Mirabella, John R Jones, Annamaria Brioli, Aneta Mikulasova, David A Cairns, Walter M Gregory, Ana Quartilho, Mark T Drayson, Nigel Russell, Gordon Cook, Graham H Jackson, Xavier Leleu, Faith E Davies, Gareth J Morgan, Brian A Walker, Eileen M Boyle, Christopher P Wardell, Alex Murison, Dil B Begum, Nasrin M Dahir, Paula Z Proszek, David C Johnson, Martin F Kaiser, Lorenzo Melchor, Lauren I Aronson, Matthew Scales, Charlotte Pawlyn, Fabio Mirabella, John R Jones, Annamaria Brioli, Aneta Mikulasova, David A Cairns, Walter M Gregory, Ana Quartilho, Mark T Drayson, Nigel Russell, Gordon Cook, Graham H Jackson, Xavier Leleu, Faith E Davies, Gareth J Morgan

Abstract

Purpose: At the molecular level, myeloma is characterized by copy number abnormalities and recurrent translocations into the immunoglobulin heavy chain locus. Novel methods, such as massively parallel sequencing, have begun to describe the pattern of tumor-acquired mutations, but their clinical relevance has yet to be established.

Methods: We performed whole-exome sequencing for 463 patients who presented with myeloma and were enrolled onto the National Cancer Research Institute Myeloma XI trial, for whom complete molecular cytogenetic and clinical outcome data were available.

Results: We identified 15 significantly mutated genes: IRF4, KRAS, NRAS, MAX, HIST1H1E, RB1, EGR1, TP53, TRAF3, FAM46C, DIS3, BRAF, LTB, CYLD, and FGFR3. The mutational spectrum is dominated by mutations in the RAS (43%) and nuclear factor-κB (17%) pathways, but although they are prognostically neutral, they could be targeted therapeutically. Mutations in CCND1 and DNA repair pathway alterations (TP53, ATM, ATR, and ZNFHX4 mutations) are associated with a negative impact on survival. In contrast, those in IRF4 and EGR1 are associated with a favorable overall survival. We combined these novel mutation risk factors with the recurrent molecular adverse features and international staging system to generate an international staging system mutation score that can identify a high-risk population of patients who experience relapse and die prematurely.

Conclusion: We have refined our understanding of genetic events in myeloma and identified clinically relevant mutations that may be used to better stratify patients at presentation.

Trial registration: ClinicalTrials.gov NCT01554852.

© 2015 by American Society of Clinical Oncology.

Figures

Figure 1
Figure 1
Correlation between mutations and recurrent cytogenetic abnormalities. Intensity of colour shade represents the degree of correlation (blue=negative and red=positive) as per scale. Only significant correlations are represented on this plot with the insignificant correlations are in white.
Figure 2
Figure 2
Impact of DNA repair pathway alterations and CKS1B copy number changes in myeloma. The prognostic impact of the number of copies of amp(1q) is greater than gain(1q) for both PFS (A) and OS (B). TP53 mutations and deletions are also associated with a significant negative impact on PFS (C) and OS (D). ATM and ATR mutations are associated with a worse outcome on both PFS (E) and OS (F).
Figure 3
Figure 3
Clinical impact and location of mutations in selected genes. Panel A: Location of the mutations and impact of ZFHX4 mutations on PFS. Panel B: Location of the mutations and impact of IRF4 mutations on OS. Panel C: Location of the mutations and impact of EGR1 mutations on OS
Figure 4
Figure 4
Results of multivariate analysis (Panel A). The ISS-MUT identifies 3 prognostic groups (Group 1: ISS I/II with no CNSA or mutation, Group 2: ISS III with no CNSA or mutation or ISS I/II/III with one CNSA or mutation, Group 3: Two CNSA or mutation regardless of their ISS). It is an efficient tool to identify independent prognostic groups in terms of PFS (Panel B) and OS (Panel C). It also identified 81% and 90% of patients that both relapse and die prematurely (panel D) The adverse features that make up the HR group in the ISS-MUT score comprises not only the traditional ISS-FISH lesions, t(4;14) and del(17p) but also a variety of lesions previously not considered in the score that account for approximately 60% of the lesions (panel E).

Source: PubMed

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